Job Title

 DATA SCIENTIST – MEDICAL IMAGING & DIAGNOSTICS (AI / DEEP LEARNING) ROLE OVERVIEW We are building next-generation AI-powered medical diagnostic solutions focused on MRI, CT, and multimodal imaging. The role involves close collaboration with radiologists, clinicians, and regulatory teams to develop clinically robust, explainable, and production-ready AI models. This position requires strong grounding in medical imaging, deep learning, and validation workflows aligned with diagnostic and regulatory standards.  KEY RESPONSIBILITIES Medical Imaging & AI Development Develop deep learning models for medical image classification, segmentation, detection, and quantitative analysis. Work extensively with MRI and CT DICOM datasets, including preprocessing, normalization, and artifact handling. Apply domain-aware image processing techniques informed by MRI/CT physics and pulse sequences. Design and train architectures such as CNNs, U-Net, ResNet, and related variants for diagnostic use cases.  Model Validation & Clinical Alignment Define and evaluate clinically relevant metrics (Dice score, sensitivity, specificity, ROC-AUC). Perform cross-dataset and cross-scanner validation to ensure robustness. Collaborate with radiologists and clinical experts to review model outputs and error cases. Implement explainability techniques such as activation maps and attention-based visualizations.  Data Engineering & Experimentation Curate, preprocess, and augment medical imaging datasets. Track experiments, datasets, and model versions using MLflow or equivalent tools. Apply statistical methods to assess model performance, bias, and stability.     Deployment & Production Develop RESTful APIs using Flask or similar frameworks for model inference. Containerize and deploy models using Docker-based workflows. Integrate models into CI/CD pipelines with proper version control and testing. Technical Skills Strong proficiency in Python with hands-on experience using PyTorch, TensorFlow, or Keras. Solid understanding of deep learning for computer vision and medical imaging. Experience handling DICOM images and medical imaging workflows. Familiarity with NumPy, OpenCV, Scikit-learn, Pandas. Experience building and deploying REST APIs. Working knowledge of MRI and CT physics, pulse sequences, and imaging artifacts. Experience applying AI to radiology use cases such as tumor detection, organ segmentation, or perfusion analysis. Software & Engineering Practices Experience with Docker, Git-based version control, and CI/CD workflows. Understanding of model testing, validation, and production readiness.  Education and Experience  Bachelor’s or Master’s degree in Biomedical Engineering, affinity towards medical image analysis, Medical Instrumentation, or related field. 2–4 years of relevant experience in medical imaging, AI, or medical device development.